Ryan Heuser is an Assistant Professor in Digital Humanities at the University of Cambridge, specializing in computational approaches to literary and intellectual history, prosody, and artificial intelligence's impact on language. His work bridges data science, machine learning, and literary studies through digital methodologies. Doctoral training in Eighteenth-Century British Literature, Stanford University (2019) Founding member & Associate Research Director, Stanford Literary Lab Junior Research Fellow, King’s College Cambridge (2019-2022) Research interests span computational modeling of semantic revolutions, large-scale literary field analysis, and the intersection of digital methods with historical and intellectual studies. His book Explorations in the Digital History of Ideas (2023) co-edited with Peter de Bolla exemplifies this approach. Recent publications focus on historical semantics, metrical analysis, and digital mapping of emotions in literature, reflecting his interdisciplinary expertise in natural language processing, network theory, and literary data visualization. Currently leads teaching initiatives at Cambridge Digital Humanities and contributes to computational projects exploring textual rhythms and large language models.
April Yi Wang is a tenure-track Assistant Professor in the Department of Computer Science at ETH Zürich, where she directs the Programming, Education, and Computer-Human Interaction Lab (PEACH Lab). She is a core faculty member at the Institute for Intelligent Interactive Systems and associated with the ETH AI Center. Wang is also an active member of ETH HCI and Swiss CHI communities, contributing significantly to human-computer interaction and educational technology research. Dr. Wang's educational background includes: Ph.D. in Information Science from University of Michigan (2023), advised by Steve Oney and Christopher Brooks M.Sc. in Computer Science from Simon Fraser University (2018), advised by Parmit Chilana B.Eng in Computer Science from Zhejiang University (2016) Dr. Wang's research focuses on human-centered approaches to programming and data science. Her work reimagines programming as a form of literature that communicates with both machines and people, exploring creative representations like text, shapes, animations, and everyday objects. She investigates how to make programming more natural and intuitive through literate programming environments, with applications in professional and educational contexts. Her research spans human-computer interaction, educational technology, and AI-assisted programming tools. Analysis of Dr. Wang's recent publications reveals a strong focus on AI-enhanced educational tools, particularly for programming and data literacy. Her work increasingly integrates large language models to scaffold learning while maintaining user agency. There's a clear trajectory toward developing situated learning approaches that connect abstract concepts to real-world contexts through augmented reality and tangible interfaces. Her research bridges HCI, education, and AI to create more accessible and engaging technical learning experiences. Dr. Wang has received numerous prestigious awards including: 2023 Gary M. Olson Award and Honourable Mention Award at ACM CHI 2022 Rising Stars in EECS and Heidelberg Laureate Forum Young Researcher 2020 Best Short Paper Award at IEEE VL/HCC and Honourable Mention at ACM CHI 2019 Best Paper Award at ACM CSCW Dr. Wang actively mentors students through thesis projects at ETH Zürich, supervising numerous bachelor's and master's students on topics ranging from AI-assisted programming to data literacy tools. Her lab, PEACH Lab, has secured funding including the recent innovedum funding for the Coducate project. She serves on program committees for major conferences including CHI and UIST, and regularly reviews for top HCI and education journals. The PEACH Lab, directed by Dr. Wang, focuses on creating expressive, intelligent, and human-centered systems that make technical topics more accessible. The lab explores textual, visual, and embodied representations for programming, with emphasis on enhancing communication, collaboration, and learning. Current research directions include balancing automation with user agency, supporting diverse learning needs, and developing tools for interdisciplinary technical communication.
Almut Sophia Koepke is a junior research group leader at the Technical University of Munich and University of Tübingen, focusing on multimodal learning problems integrating sound, vision, and text. Her work bridges foundational research in audio-visual understanding with practical applications in few-shot learning, zero-shot translation, and cross-modal attention mechanisms.
Fabian Fagerholm is an Assistant Professor in the Department of Computer Science at Aalto University. His work bridges software engineering, human-computer interaction, and empirical research methodologies. He actively participates in research groups such as Software and Service Engineering (SSE) and Human-Computer Interaction and Design (HCID). Fagerholm's research explores: Continuous experimentation in software development Developer cognition and mental models Agile methodologies and team dynamics Low-code platforms and end-user programming Software engineering education and pedagogy His publications reflect a strong empirical focus, with recurring themes of human factors in technical systems and educational innovation. He has received notable awards including: Journal of Systems and Software Best Paper Award (2018) EUROMICRO SEAA Distinguished Paper Award (2017) Teacher of the Year (2013) Nokia Foundation Scholarship (2013) Fagerholm contributes to software engineering infrastructure through tools for experimentation and boundary artifacts, enhancing collaboration in distributed teams.
Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).
Janna Parker is a professor in the Department of Marketing at James Madison University, specializing in digital marketing, retailing, and nonprofit marketing. With a career transition from political campaigns, she focuses on social media's role in personal and professional branding. Her research examines work-personal social media boundaries, employer governance policies, and volunteerism in nonprofit contexts. Education: Bachelor's in History (California State University Sacramento), Master's (Cameron University), Doctorate (Louisiana Tech) Teaching Interests: Digital marketing education, social media strategy, nonprofit marketing Her scholarly work spans social media governance, volunteer engagement, and retail dynamics, with recent emphasis on digital marketing pedagogy and cancel culture implications. Parker has contributed to academic journals through empirical studies and conceptual commentaries. Key article trends include: Digital marketing education evolution (2024) Social media governance in corporate and nonprofit contexts (2024) Online teaching satisfaction in higher education (2022) Volunteer brand community dynamics (2020) Consumer behavior frameworks (2019) Her media appearances include expert commentary on holiday retail strategies and social media research, reflecting practical applications of her academic work.
Vicente Talanquer is a University Distinguished Professor in the Department of Chemistry and Biochemistry at the University of Arizona, College of Science. His academic journey includes a B.S., M.A., and Ph.D. in Chemistry from the Universidad Nacional Autónoma de México (UNAM), followed by postdoctoral research at the University of Chicago's James Frank Institute. He has held various academic roles, including Professor and Associate Professor at UNAM before joining the University of Arizona in 2000. His research focuses on chemistry education, particularly student reasoning, assessment, and the development of chemical thinking. Key areas include understanding how students conceptualize chemical reactions, design learning progressions, and improve formative assessment strategies. He has led initiatives such as the Instructional-Teams Model to enhance teaching practices in STEM courses. Dr. Talanquer has received numerous awards, including the ACS Award for Achievement in Research (2021) and Arizona Professor of the Year (2015). He actively contributes to national and international educational committees, editorial boards, and professional societies such as the American Chemical Society and NARST. His work emphasizes curriculum innovation, teacher preparation, and fostering equity in science education. His research is supported by grants from the National Science Foundation and the UA Provost Investment Fund, focusing on active learning, large-enrollment course redesign, and systems thinking approaches. Talanquer's publications span over 200 peer-reviewed articles, textbooks, and educational resources in chemistry education, reflecting his commitment to advancing both research and practice in the field.
Cathryn Carson is a Professor in the Department of History at the University of California, Berkeley. Her work bridges the philosophical, cultural, and political dimensions of 20th-century science, with a focus on theoretical physics, nuclear history, and the integration of social sciences and humanities into engineering education. Education: AB in History and Philosophy of Science from University of Chicago (1990) AM in Physics from Harvard University (1993) PhD in History of Science from Harvard University (1995) Her research explores the interplay between science and philosophy, particularly in Germany and the U.S., alongside the institutionalization of data science. She teaches graduate and undergraduate courses, including Berkeley’s Data Science major’s Human Contexts and Ethics of Data course. Scientific Awards: Berkeley Collegium Award for Excellence in Undergraduate Education (2017) Distinguished Service Award, Division of Social Sciences (2014) Carol D. Soc Distinguished Graduate Student Mentoring Award (2014) Fellow of the American Association for the Advancement of Science Fellow of the American Physical Society Mellon New Directions Fellowship NSF CAREER Award Alexander von Humboldt Foundation Research Fellowship Member, Institute for Advanced Study, Princeton Carson has served in multiple leadership roles, including Associate Dean of Social Sciences, founding Interim Director of the D-Lab (Social Science Data Laboratory), and Faculty Lead of Berkeley’s Data Science Education Program. She is currently accepting students for advising and contributes to campus governance through roles in the Academic Senate.
Nima Mesgarani is an Associate Professor of Electrical Engineering at Columbia Engineering, Columbia University, affiliated with the Sense, Collect and Move Data Committee. His research bridges engineering and neuroscience through reverse-engineering neural signal processing mechanisms, leading to advancements in brain-machine interfaces, neural prosthetics, and speech processing algorithms. He received his PhD in Electrical Engineering from the University of Maryland and completed postdoctoral training at Johns Hopkins University's Center for Language and Speech Processing and UC San Francisco's Neurosurgery Department. Research Focus Professor Mesgarani's lab integrates computational neuroscience and engineering to study acoustic signal processing. Key areas include: Neural decoding of speech and auditory attention in multi-talker environments Development of brain-controlled hearing technologies Novel speech separation and synthesis algorithms inspired by cortical processing Cross-modal learning between auditory and visual systems Applications of large language models in neural signal interpretation Publication Trends Analysis of his 15 most recent articles (2025) reveals dominant themes: neural decoding techniques using intracranial EEG, brain-inspired speech separation models (e.g., Mamba architectures), applications of large language models in auditory neuroscience, cross-modal distillation methods, and clinical translation of audio processing algorithms. A strong emphasis emerges on real-time brain-computer interfaces and noise-robust speech processing. Laboratory and Collaborations Mesgarani directs an interdisciplinary lab developing neurotechnology for hearing restoration. His team collaborates with neurosurgery departments and speech processing centers, focusing on translating theoretical models into clinical brain-machine interfaces. The lab's work has yielded patents for brain-informed speech separation systems and attention-decoding frameworks.
Prof. Bernt Schiele is a Max Planck Director at the Max Planck Institute for Informatics and holds a Professorship at Saarland University. His research focuses on understanding multimodal sensor data, with key areas in computer vision, 3D object recognition, and machine learning. He leads the Computer Vision and Machine Learning group, addressing challenges in sensor fusion, scene understanding, and human activity recognition. Schiele has held academic roles at TU Darmstadt, ETH Zurich, and MIT, and contributes to top journals like IEEE Transactions on PAMI and conferences like ECCV. His work emphasizes robust models, interpretability, and domain adaptation for real-world applications. Education: PhD (1997, Grenoble), MSc (1994 Karlsruhe/1993 Grenoble) Key Positions: MIT (1997-2000), ETH Zurich (1999-2004), TU Darmstadt (2004-2010) Research interests span 3D scene understanding, multimodal sensor processing, and machine learning techniques for large-scale data. His recent work advances robust object detection, explainable AI, and domain-invariant training methods. He also chairs major conferences like ECCV 2018 and co-chairs ICCV 2011. Publications highlight innovations in interpretable vision transformers, certified explanations, and test-time adaptation. Despite no listed awards, his contributions shape foundational areas of computer vision and multimodal AI.
Prof. Dr. André Bardow is a Full Professor in Energy and Process Systems Engineering at ETH Zurich , leading research at the intersection of thermodynamics, machine learning, and sustainable energy systems. Previously, he held professorships at RWTH Aachen University (2010-2020) and TU Delft (2007-2010). He also served as part-time director at Forschungszentrum Jülich (2017-2022) and visiting professor at UC Santa Barbara (2015/16). His work focuses on energy systems optimization , computer-aided molecular design , and CO2 capture & utilization . PhD from RWTH Aachen University Current ETH Zurich affiliation Former roles at RWTH Aachen, TU Delft, Jülich Research Center His research integrates machine learning with thermodynamic modeling to optimize processes like crystallization and electrochemical cooling . Recent publications demonstrate advancements in solvent design, CO2 transport LCA, and ORC working fluid optimization. He chairs the VDI Technical Committee for Thermodynamics (2016-2024) and has received multiple awards including the Covestro Science Award and Arnold-Eucken-Award . Current projects address carbon circular economies , electrified chemical production , and AI-driven process optimization . His lab at ETH Zurich develops cutting-edge technologies like ML-CAMPD frameworks for sustainable separation processes and photoacid-based CO2 capture systems. Funding from the H2020 Systemic Expansion of Circular Ecosystems (grant 101036854) supports these initiatives. 2024 Clarivate Highly Cited Researcher 2022 Inaugural Lecture: "To sustainability and beyond: A computer-animated story on energy & chemicals" Recipient of multiple teaching and research excellence awards
Larissa Schlegel-Pape serves as a Scientific Associate at the Department for Ornamental and Pedigree Poultry within the Farm Animal Clinic of Freie Universität Berlin's Faculty of Veterinary Medicine. Her work focuses on developing innovative methods for assessing chicken welfare through the creation of the "Stressed Chicken Scale," which aims to systematically identify stress indicators in poultry. Her research interests center on animal welfare science, specifically stress assessment in chickens using both behavioral observation and computer vision technology. She investigates how body posture, movement patterns, and other visual indicators can reliably signal discomfort or stress in poultry, with the goal of creating practical assessment tools for veterinarians and poultry farmers. Her work bridges veterinary medicine, ethology, and technological innovation, contributing to refinement research (one of the 3Rs principles) in animal husbandry. Analysis of her publications reveals a strong focus on developing and validating the Stressed Chicken Scale across multiple contexts. Her work spans methodological development, practical implementation studies, and technological integration with computer vision systems. The research demonstrates progression from conceptual framework to validation studies and practical application, with increasing sophistication in assessment techniques and broader implications for animal welfare standards in poultry farming. Schlegel-Pape actively collaborates with the Federal Institute for Risk Assessment (BfR) and participates in interdisciplinary projects involving artificial intelligence applications in agriculture. She presents her findings regularly at major German veterinary conferences including the DVG (Deutsche Veterinärmedizinische Gesellschaft) events, DACh Epidemiology conferences, and specialized poultry medicine gatherings. Her work contributes significantly to advancing animal welfare assessment methodologies and promoting refinement in poultry husbandry practices.
Paulo Blikstein serves as Associate Professor of Communications, Media and Learning Technology Design at Columbia University. Previously, he was Assistant Professor of Education and (by courtesy) Computer Science at Stanford University and co-founded the Lemann Center for Brazilian Education (2008-2018). Education: Ph.D. in Learning Sciences, Northwestern University (2009) M.A. in Media Arts & Sciences, MIT Media Lab (2002) M.Eng. in Electronic Engineering, University of São Paulo (2000) B.S. in Metallurgical Engineering, University of São Paulo (1998) His research pioneers constructionist learning environments through digital fabrication, educational robotics, and tangible interfaces—focusing on equitable access for underserved communities. Inspired by Paulo Freire and Seymour Papert, he develops open-source tools like the GoGo Board robotics platform and leads the global FabLab@School initiative establishing fabrication labs in schools across four continents. Current work emphasizes multimodal learning analytics to study student interactions in maker-centered classrooms. Publications reveal strong focus on democratizing invention through maker education, with recurring themes in constructionist theory application, multimodal assessment, and context-specific technology adaptation. Brazilian education reform and low-cost computational solutions form significant threads, particularly in 2016-2017 publications. Scientific Awards: Two Google Faculty Awards National Science Foundation Early Career Award (highest U.S. government honor for early-career scientists) Blikstein directs the Transformative Learning Technologies Lab (TLTL) and co-founded Stanford's Center for Educational Entrepreneurship and Innovation in Brazil. His FabLearn conference established the first academic forum on Maker Movement applications in education. While specific grant details aren't listed, the NSF CAREER Award signifies major federal research funding. He spearheads the FabLab@School project deploying advanced fabrication labs in K-12 institutions worldwide and founded the FabLearn conference series. His work integrates teams of engineers, educators, and designers to create scalable solutions for resource-constrained learning environments.
Vincent Kaufmann is an Associate Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) , leading the Urban Sociology Laboratory (LaSUR) . Since 2010, he serves as Scientific Director of the Mobile Lives Forum in Paris. His career spans teaching at institutions like Lancaster University , Ecole des Ponts ParisTech , and Tongji University , with research focusing on mobility sociology , urban dynamics , and public policy evaluation . Master's in Sociology from University of Geneva PhD at EPFL on transport modal practices His work explores mobility-capital interactions , motility , and rhythmanalysis in contemporary societies. Key themes include urban lifestyle transformations , cross-border regions , and mobility-sustainability nexus , with recent emphasis on new proximities and slow cities . Teaching roles span EPFL departments like Teaching (EDAR) , Architecture and Urban Sciences (SGC) , and Human and Social Sciences (CDH) . He has directed numerous PhD and master's theses on urban mobility topics.
Prof. Dr. Mirko Hornung is a Professor of Aircraft Design at the TUM School of Engineering and Design, Technische Universität München. His research focuses on conceptual aircraft design, integration of propulsion systems, and evaluation of aviation technologies in operational contexts. Education and Career: PhD in Aeronautical Engineering from the University of the Bundeswehr (2003), awarded a research prize for work on reusable space transport systems. 2003–2009: Worked at Airbus Group (EADS) on military air systems, propulsion integration, and program management. Executive Director of Research & Technology at Bauhaus Luftfahrt, a think tank for long-term aviation developments. Research Interests: Aircraft design optimization, including hybrid energy systems, electric propulsion, and UAV technologies. Environmental sustainability in aviation, such as hydrogen-powered aircraft and lifecycle assessment. Aerodynamic and structural analysis, including flutter suppression and composite materials. Key Publications Highlight Trends: Focus on hybrid-electric and hydrogen propulsion for reducing environmental impact. Advancements in UAV design, including morphing wings and autonomous systems. Integration of AI-driven tools for propulsion optimization and lifecycle analysis. Scientific Awards: EADS Promotion Award (1995) Research Prize for Thesis on Reusable Space Transport Systems (2003) Advising & Grants: Directs research at Bauhaus Luftfahrt, collaborating on future aviation concepts. Engaged in interdisciplinary projects like FLEXOP UAV demonstrator and Ce-Liner eMobility studies. Labs/Teams: Active in the Aircraft Design Professorship at TUM and leadership roles at Bauhaus Luftfahrt, focusing on next-generation aviation technologies.
